In this project, education researchers, environmental scientists, and educators will develop a computer tool to let STEM educators and curriculum developers build local environmental science models. The system will use data about land use to automatically construct map-based simulations of any area in the United States. Users will be able to choose from a range of environmental and economic issues to include in these models. The system will create simulations that ask students to change to patterns of land use -- for example, increasing land zoned for housing, or open land, or industrial development -- to try to meet environmental and social goals. As a result, students will be able to learn about the interaction of environmental and economic issues relevant to their own city, town, neighborhood, or region. These map-based simulations will be incorporated into an existing science, technology, engineering, and mathematics (STEM) education tool, Land Science, in which learners work in a fictional planning office to study how zoning affects economic and environmental issues in a community. Research has shown that Land Science is mode effective when learners are exploring issues in an area near their home, and the current study will investigate how and why local simulations improve environmental science learning. This project is funded by the Advancing Informal STEM Learning (AISL) program which supports work to enhance learning in informal environments by funding innovative research, approaches, and resources for use in a variety of settings.
In this project, the research team will build, test, and deploy a toolkit that will allow informal STEM educators and developers of informal STEM programming to easily adapt an existing environmental science learning environment, which consists of a place-based virtual internship in urban planning and ecology, to their local contexts, learning objectives, and learner populations. Land Science is a virtual internship in which young people explore the environmental and socio-economic impacts of land-use decisions. To do so, they play the role of interns at an urban planning firm developing a new land-use proposal for the city of Lowell, Massachusetts: they read reports, virtually visit sites, determine stakeholder priorities, and use a geographic information system (GIS) model to evaluate the socio-economic and environmental impacts of land-use choices. No one plan can satisfy all stakeholders, so learners must compromise to create an effective plan and justify their decisions. Land Science has been shown to improve civic engagement, interest in eco-social issues, and understanding of scientific models, but it is most effective when the location of the virtual internship is in or near the learners' home town. To improve the accessibility and impact of this effective learning intervention, the interdisciplinary research team, which includes learning scientists, land-use experts, and informal STEM educators, will develop a Local Environmental Modeling toolkit, which will allow educators to change the location of the simulation and the stakeholder groups, zoning codes, and environmental and socio-economic indicators included in the land-use model. The system will ensure that the model produced is functional, realistic, and appropriately complex. The localized versions of Land Science produced by informal STEM educators will be used in a range of contexts and locations, allowing the research team to study the effects of an online, place-based learning intervention on environmental science learning, STEM interest and motivation, and civic engagement.
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TEAM MEMBERS:
David ShafferKristen ScopinichHolly GibbsJeffrey Linderoth
Metaphors and visualizations are important for science communication, though they may have limitations. This paper describes the development and evaluation of a novel interactive visualization, the "Dynamic Evolutionary Map"' (DEM), which communicates biological evolution using a non-standard metaphor. The DEM uses a map metaphor and interactivity to address conceptual limitations of traditional tree-based evolutionary representations. In a pilot evaluation biology novices used the DEM to answer questions about evolution. The results suggest that this visualization communicates some conceptual